✦ LIBER ✦

LOCALLY WEIGHTED LEAST SQUARES KERNEL REGRESSION AND STATISTICAL EVALUATION OF LIDAR MEASUREMENTS

✍ Scribed by ULLA HOLST; OLA HÖSSJER; CLAES BJÖRKLUND; PÄR RAGNARSON; HANS EDNER

Publisher: John Wiley and Sons
Year: 1996
Tongue: English
Weight: 702 KB
Volume: 7
Category: Article
ISSN: 1180-4009
DOI: 10.1002/(sici)1099-095x(199607)7:4<401::aid-env221>3.0.co;2-d

No coin nor oath required. For personal study only.

✦ Synopsis

The LIDAR technique is an efficient tool in monitoring the distribution of atmospheric species of importance. We study the concentration of atmospheric atomic mercury in an Italian geothermal field and discuss the possibility of using recent results from local polynomial kernel regression theory for the evaluation ofthe derivative of the DIAL curve. A MISE-optimal bandwidth selector, which takes account of the heteroscedasticity in the regression is suggested. Further, we estimate the integrated amount of mercury in a certain area.